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  <div class="section" id="geosnap-analyze-analytics-affinity-propagation">
<h1>geosnap.analyze.analytics.affinity_propagation<a class="headerlink" href="#geosnap-analyze-analytics-affinity-propagation" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="geosnap.analyze.analytics.affinity_propagation">
<code class="sig-prename descclassname">geosnap.analyze.analytics.</code><code class="sig-name descname">affinity_propagation</code><span class="sig-paren">(</span><em class="sig-param">X</em>, <em class="sig-param">damping=0.8</em>, <em class="sig-param">preference=-1000</em>, <em class="sig-param">max_iter=500</em>, <em class="sig-param">convergence_iter=15</em>, <em class="sig-param">copy=True</em>, <em class="sig-param">affinity='euclidean'</em>, <em class="sig-param">verbose=False</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/geosnap/analyze/cluster.html#affinity_propagation"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#geosnap.analyze.analytics.affinity_propagation" title="Permalink to this definition">¶</a></dt>
<dd><p>Clustering with Affinity Propagation.</p>
<dl class="field-list">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl>
<dt><strong>X</strong><span class="classifier"><a class="reference external" href="https://docs.scipy.org/doc/numpy/glossary.html#term-array-like" title="(in NumPy v1.17)"><span>array_like</span></a></span></dt><dd><p>n x k attribute data</p>
</dd>
<dt><strong>preference</strong><span class="classifier"><a class="reference external" href="https://docs.scipy.org/doc/numpy/glossary.html#term-array-like" title="(in NumPy v1.17)"><span>array_like</span></a>, shape (n_samples,) or <a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.8)"><code class="docutils literal notranslate"><span class="pre">float</span></code></a>, optional, default: <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.8)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>The preference parameter passed to scikit-learn’s affinity propagation
algorithm</p>
</dd>
<dt><strong>damping</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.8)"><code class="docutils literal notranslate"><span class="pre">float</span></code></a>, optional, default: 0.8</span></dt><dd><p>The damping parameter passed to scikit-learn’s affinity propagation
algorithm</p>
</dd>
<dt><strong>max_iter</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.8)"><code class="docutils literal notranslate"><span class="pre">int</span></code></a>, optional, default: 1000</span></dt><dd><p>Maximum number of iterations</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl>
<dt><strong>fitted cluster instance</strong><span class="classifier"><a class="reference external" href="https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AffinityPropagation.html#sklearn.cluster.AffinityPropagation" title="(in scikit-learn v0.22)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sklearn.cluster.AffinityPropagation</span></code></a></span></dt><dd></dd>
</dl>
</dd>
</dl>
</dd></dl>

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